We're an AI first company transforming the food supply chain and scaling up rapidly to meet the needs of larger distributors in the industry.
My team is responsible for scalability, reliability and pretty much every other non-product task that comes up day to day. You'll get to work with a top class group of people and lead on making our systems 10x better than they were.
Submit here (or ping me):
https://app.careerpuck.com/job-board/choco/job/079ab75d-8de9...
We do enterprise document ingestion — capture a document once into a canonical field registry, then project it to any schema, no re-extraction. Stack: AWS, Docker, Railway.
We've never had a dedicated reliability owner and it's starting to show. You'd be the first: SLOs and an error-budget policy that actually gets honoured, observability worth paging on, post-mortems that change the architecture, deploys nobody dreads. Target is 99.9%. Compliance is real here (GDPR, ISO 27001/42001, HIPAA), so reliability and audit work overlap.
Haven't used Railway? Fine, we'll onboard you. We ship with Claude Code day to day — if that's interesting rather than irritating, good.
Process: founder chat (bring a Sev1 you've owned), a paid day building with us on something real, team fit, references.
Hi HN! I'm Seema, Tech Recruiter at Ojin, and we're looking for another Product Engineer to join our small team.
We build the infrastructure that makes AI feel human — real-time AI agents with natural, lifelike conversation on a globally distributed GPU fabric. We've spent 5+ years proving this works for enterprise customers and we're now opening it up as a developer platform.
You'd own features end-to-end: interactive frontends through to Python-based agentic backends, working directly with the founders on a 15 person team. You help define the solution, design the architecture and ship it.
Stack: TypeScript, React, Node.js, Python, WebRTC, WebSockets, AWS
Looking for: 3-5 years, genuine full-stack ability, startup experience and genuine curiosity about how AI systems actually work in production.
We're not able to offer visa sponsorship or relocation support for this role - you'll need to already be based within CET ±2h and have the right to work where you live.
Apply or read more about us here: https://ojin.ai
Thank you!
Hi, I'm Max, CTO and co-founder. Langfuse is the open-source LLM engineering platform — tracing/observability, evals, and prompt management — used by tens of thousands of teams to ship, debug, and improve their LLM and agent apps.
Earlier this year, Langfuse joined ClickHouse ($400M Series D led by Dragoneer, $15B valuation). That gives us the best of both worlds: startup-speed, ownership, and roadmap control, backed by the scale, resources, and equity upside of a category-defining infra company.
The full story: Why we joined: https://langfuse.com/blog/joining-clickhouse ClickHouse's take: https://clickhouse.com/blog/clickhouse-acquires-langfuse-ope...
Right now we're focused on helping customers segment their traces, surface insights from them, and ship changes to their agents faster — observability at serious scale, plus the product surface engineers actually live in day to day. See what we're building: langfuse.com
Our handbook is the best way to understand how we operate: https://langfuse.com/handbook
Check out our open roles and apply to the one you think fits you best and we'll take it from there: https://langfuse.com/careers. Happy to answer questions in the thread.
We are an AI engineering company that builds end-to-end AI solutions. By applying the latest AI research, we keep our clients at the forefront of innovation. If you are interested check out:
https://www.ml6.eu/en/customers/cases/
Work on innovative projects for the biggest clients across Europe such as Randstad, ASML, FUNKE, and many more! Whether it’s about leveraging LLMs to improve customer support, building data lakes on cloud platforms to improve storage or implementing models using sensor data for quality control. You can find it all at ML6. You will mostly work with Python and a range of ML frameworks such as TensorFlow, PyTorch, or HuggingFace Transformers and help bring application into production by building data pipelines and cloud infrastructure on all of the major cloud providers (GCP, AWS, Azure).
Open roles include:
• Senior AI Engineer
• Senior Software Engineer
• Medior AI Engineer
• Squad Lead GenAI
and many more!
Apply now at the https://jobs.ml6.eu/
Mitte is an AI creative suite — the agentic OS for creative teams.
Engineering (Berlin, on-site):
- Senior Full-Stack Engineer (Go, React): https://mitte.ai/careers/role/GZHn1_O6 - Senior Frontend Engineer (React, TS, Redux): https://mitte.ai/careers/role/5qi8KR4D - Senior Backend Engineer (Elixir, Go): https://mitte.ai/careers/role/oaFnPm0A - Founding Engineer (Go, React): https://mitte.ai/careers/role/7VTbvOaeWe build Haystack, an open source LLM framework, and the enterprise platform on top of it. Focus is sovereign AI, on-prem and VPC deployments for organizations that need to run LLMs on their own infrastructure rather than call an external API.
If you want to be part of Europe's push toward AI sovereignty and are looking for complex, high-stakes problems we'd love to hear from you.
Apply: https://jobs.ashbyhq.com/deepsetai?utm_source=hackernews Or reach out directly: https://bit.ly/juliaLN
Deep learning transformed text and images but mostly skipped tables - the data behind most clinical trials, financial models, and scientific experiments. The reason is structural: no natural sequence, no spatial structure, no shared vocabulary across datasets, so the architectures and scaling laws behind LLMs don't transfer.
Our approach: pre-train a transformer on millions of synthetic datasets sampled from causal-structure priors. Your whole dataset goes in as context, predictions come out in a single forward pass - no per-dataset training, no hyperparameter tuning, seconds instead of hours. It works: TabPFN v2 was published in Nature and set a new state of the art; TabPFN-3 scales to 10M rows. 4M+ downloads, 8k+ GitHub stars, production use from liquid biopsy to rail maintenance. As of last month we're an independent lab inside SAP, backed by €1B+ - models stay open, research stays public, same team and offices.
Open roles (most can sit in any of our three offices):
Senior ML Infrastructure Engineer - own multi-cluster GPU infra (Slurm on GCP today, multi-provider next), training performance, and the tooling layer. We spend tens of millions/year on compute; you own that budget.
Research Scientist, Foundation Model - drive the model agenda: novel architectures, scaling 10K to 1M+ samples, multimodal and causal directions. PhD + top-venue publications or equivalent.
Research Engineer, Foundation Model - same agenda from the engineering side: you design experiments, write the training and eval infra, and co-author the papers.
ML Engineer, Cloud Platform - design and scale the backend that serves and finetunes the models. Python/FastAPI, Terraform, K8s.
Full Stack Engineer, ML Platform - build the product end to end. TS + Python, React/FastAPI/Postgres.
Also hiring: Applied Scientist, Forward Deployed ML Engineer, Research Scientist (Foundational Data Science), PhD research interns, plus GTM and ops roles.
~40-person team with backgrounds from Google, DeepMind, Jane Street, Goldman, G-Research, CERN. Led by Frank Hutter, advised by Bernhard Schölkopf and Yann LeCun. Comp competitive with top AI labs.
All roles: https://jobs.ashbyhq.com/prior-labs